Myeloid Leukemia

Classification of AML by DNA-Oligonucleotide Microarrays 231
Fig. 3. Hierarchical cluster analysis workflow. The primary expression data are
graphically represented. Each data point is represented with a color that quantitatively
and qualitatively reflects the original measured fluorescence intensity. One can look at
such images, identify patterns or branches of the dendrogram of interest, and readily
zoom in on the detailed expression patterns and identities of the genes contributing to
these patterns.
is scanned to identify the highest value that represents the most similar pair of
genes. Then a node is created joining these two genes, and a gene expression
profile is computed for the node by averaging observations for the joined elements.
The similarity matrix is updated with this new node replacing the two
joined elements, and the process is repeated n – 1 times until only a single
element remains.
Any unsupervised gene expression analysis begins with a definition of similarity
between expression patterns, but with no prior knowledge of the true
functional classes of the genes, or patients, respectively. For visualization of